FRRI：一种新颖的模糊粗糙规则归纳算法
FRRI: a novel algorithm for fuzzy-rough rule induction
AI总结：
本文提出了一种名为FRRI的新型模糊粗糙规则归纳算法，结合模糊集与粗糙集理论，实验表明其在准确性和规则集简洁性上优于现有方法。
摘要：
可解释性是机器学习研究的下一个前沿。在寻找白盒模型的过程中——与随机森林或神经网络等黑盒模型相对——规则归纳算法是一个合乎逻辑且充满前景的选择，因为这些规则很容易被人类理解。模糊集和粗糙集理论已被成功应用于这一原型，但几乎总是分开使用。由于这两种规则归纳方法都涉及基于等价类概念的粒计算，将它们结合起来是很自然的。QuickRules算法是利用模糊粗糙集理论进行规则归纳的首次尝试。它基于QuickReduct，这是一种用于构建决策约简的贪心算法。QuickRules已经显示出对其他规则归纳方法的改进。然而，要评估模糊粗糙规则归纳算法的全部潜力，需要从基础开始。在本文中，我们引入了一种名为Fuzzy Rough Rule Induction（FRRI）的新型规则归纳算法。我们提供了背景知识并解释了算法的工作原理。此外，我们进行了计算实验来评估算法的性能，并将其与其他最先进的规则归纳方法进行比较。我们发现，我们的算法在创建由相对较短的规则组成的小型规则集时更加准确。我们最后概述了未来工作的一些方向。
英文摘要：
Interpretability is the next frontier in machine learning research. In the search for white box models - as opposed to black box models, like random forests or neural networks - rule induction algorithms are a logical and promising option, since the rules can easily be understood by humans. Fuzzy and rough set theory have been successfully applied to this archetype, almost always separately. As both approaches to rule induction involve granular computing based on the concept of equivalence classes, it is natural to combine them. The QuickRules\cite{JensenCornelis2009} algorithm was a first attempt at using fuzzy rough set theory for rule induction. It is based on QuickReduct, a greedy algorithm for building decision reducts. QuickRules already showed an improvement over other rule induction methods. However, to evaluate the full potential of a fuzzy rough rule induction algorithm, one needs to start from the foundations. In this paper, we introduce a novel rule induction algorithm called Fuzzy Rough Rule Induction (FRRI). We provide background and explain the workings of our algorithm. Furthermore, we perform a computational experiment to evaluate the performance of our algorithm and compare it to other state-of-the-art rule induction approaches. We find that our algorithm is more accurate while creating small rulesets consisting of relatively short rules. We end the paper by outlining some directions for future work.
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